Closeness matters. Spatial autocorrelation and relationship between socioeconomic indices and distance to departmental Colombian capitals

Socioeconomic indices that developing economies use to combat poverty may show a limited picture of all the variables related to the problem. This study analyzes spatial autocorrelation and clusters of three socioeconomic indices—living conditions, multidimensional poverty, and unsatisfied basic needs—in Colombia to explore the relation of the identified clusters with their physical distance from departmental capitals. Using a local index of spatial autocorrelation, it evaluates spatial patterns and the clustering of socioeconomic indices. Correlation analysis tests the relation between clusters and their distance from departmental capitals in three departments. The spatial patterns of indices in Colombia correspond to the model of economic development in the country and reveal the regions where socioeconomic characteristics form clusters of desirable/undesirable conditions and departments where the distance from main cities may be seen as a condition for a higher quality of life.